Catálogo de publicaciones - libros

Shape from silhouettes is a binary geometric tomography since both objects and projections, which are measured as silhouettes, are binary. In this paper, we formulate shape from silhouettes in the three-dimensional discrete space. This treatment of the problem implies an ambiguity theorem for the reconstruction of objects in discrete space. Furthermore, we show that in three-dimensional space, it is possible to reconstruct a class of non-convex objects from a collection of silhouettes though on a plane non-convex object is unreconstractable from any collection of silhouettes.

The present paper deals with discrete lines in the 3-dimensional space. In particular, we focus on the minimal 0-connected set of closest integer points to a Euclidean line. We propose a definition which leads to geometric, arithmetic and algorithmic characterizations of naive discrete lines in the 3-dimensional space.

This paper discusses general object recognition by using image set in the scenario where multiple shots are available for each object. As a way of matching sets of images, canonical correlations offer many benefits in accuracy, efficiency, and robustness compared to the classical parametric distribution-based and non-parametric sample-based methods. However, it is essentially an representative but not a discriminative way for all the previous methods in using canonical correlations for comparing sets of images. Our purpose is to define a transformation such that, in the transformed space, the sum of canonical correlations (the cosine value of the principle angles between any two subspaces) of the intra-class image sets can be minimized and meantime the sum of canonical correlations of the inter-class image sets can be maximized. This is done by learning a margin-maximized linear discriminant function of the canonical correlations. Finally, this transformation is derived by a novel iterative optimization process. In this way, a discriminative way of using canonical correlations is presented. The proposed method significantly outperforms the state-of-the-art methods for two different object recognition problems on two large databases: a celebrity face database which is constructed using Image Google and the ALOI database of generic objects where hundreds of sets of images are taken at different views.

A 3D Partitioned Active Shape Model (PASM) is proposed in this paper to address the problems of 3D Active Shape Models (ASM) caused by the limited numbers of training samples, which is usually the case in 3D segmentation. When training sets are small, 3D ASMs tend to be restrictive, because the plausible area/allowable region spanned by relatively few eigenvectors cannot capture the full range of shape variability. 3D PASMs overcome this limitation by using a partitioned representation of the ASM. Given a Point Distribution Model (PDM), the mean mesh is partitioned into a group of small tiles. The statistical priors of tiles are estimated by applying Principal Component Analysis to each tile to constrain corresponding tiles during deformation. To avoid the inconsistency of shapes between tiles, samples are projected as curves in one hyperspace, instead of point clouds in several hyperspaces. The deformed model points are then fitted into the allowable region of the model by using a curve alignment scheme. The experiments on 3D human brain MRIs show that when the numbers of the training samples are limited, the 3D PASMs significantly improve the segmentation results as compared to 3D ASMs and 3D Hierarchical ASMs, which are the extension of the 2D Hierarchical ASM to the 3D case.

Most patch based image completion algorithms fill in missing parts of images by copying patches from the known part of the image into the unknown part. The criterion for preferring one patch over another is the compatibility or consistency of the proposed patch with the nearby region that is known or already completed. In this paper we propose adding another dimension to this consistency criterion, namely, scale. Thus, the preferred patch is chosen by evaluating its consistency with respect to smoothed (less detailed) versions of the image, as well as its surroundings in the current version. Applied recursively, this approach results in a multi-scale framework that is shown to yield a dramatic improvement in the robustness of a good existing image completion algorithm.

Prosperity of distributed 3D applications on the Web heavily depends on the portability and reusability of the content created. Currently, Web3d formats often fall short in resolving such issues. This paper introduces EXDRAP as a hybrid publishing paradigm for declaratively creating Web-based collaborative virtual reality applications which we believe improves portability and reusability. The major issues concerning the development of Web-based CVEs are closely investigated; and an extended technique and an optimizing translation mechanism are proposed which reduce the latency (lag) and the amount of memory taken by the browser, respectively. Based on X3D (the successor to VRML) as the ISO standard for real-time computer graphics on the Web, the concepts are successfully implemented and integrated into Jakarta Struts Framework. In order to gain maximum portability, the integration of the X3D browser and the server-side technology is made possible through the use of ECMAScript instead of java on the client end.

The presentation of Bézier surfaces affects the results of rendering and tessellating applications greatly. To achieve optimal parameterization, we present two reparameterization algorithms using linear Möbius transformations and quadratic transformations, respectively. The quadratic reparameterization algorithm can produce more satisfying results than the Möbius reparameterization algorithm with degree elevation cost. Examples are given to show the performance of our algorithms for rendering and tessellating applications.

An algorithm for constructing constrained Delaunay triangulation (CDT) of a planar straight-line graph (PSLG) is presented. Although the uniform grid method can reduce the time cost of visibility determinations, the time needed to construct the CDT is still long. The algorithm proposed in this paper decreases the number of edges involved in the computation of visibility by replacing traditional visibility with Delaunay visibility. With Delaunay visibility introduced, all strongly Delaunay edges are excluded from the computation of visibility. Furthermore, a sufficient condition for DT (CDT whose triangles are all Delaunay) existence is presented to decrease the times of visibility determinations. The mesh generator is robust and exhibits a linear time complexity for randomly generated PSLGs.

In a collaborative system, the level of co-presence, the feeling of being with the remote participants in the same working environment, is very important for natural and efficient task performance. One way to achieve such co-presence is to recreate the participants as real as possible, for instance, with the 3D whole body representation. In this paper, we introduce a method to recreate and immerse tele-operators in a collaborative augmented reality (AR) environment. The method starts with capturing the 3D cloud points of the remote operators and reconstructs them in the shared environment in real time. In order to realize interaction among the participants, the operator’s motion is tracked using a feature extraction and point matching (PM) algorithm. With the participant tracking, various types of 3D interaction become possible.

Object segmentation is a crucial task for image analysis and has been studied widely in the past. Most segmentation algorithms rely on changes in contrast or on clustering the same colors only. Yet there seem to be no real one-and-for-all solution to the problem. Nevertheless graph-based energy minimization techniques have been proven to yield very good results in comparison to other techniques. They combine contrast and color information into an energy minimization criterion. We give a brief overview of two recently proposed techniques and present some enhancements to them. Furthermore a combination of them into the algorithm leads to suitable results for segmenting objects in infrared images.